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<div class="title">sac_model_line.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *  Copyright (c) 2009, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *  Copyright (c) 2012-, Open Perception, Inc.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *  All rights reserved.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *  Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *  modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *  are met:</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *   * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *     notice, this list of conditions and the following disclaimer.</span></div>
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<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="comment"> */</span></div>
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<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#ifndef PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_LINE_H_</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="preprocessor">#define PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_LINE_H_</span></div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160; </div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#include &lt;pcl/sample_consensus/sac_model_line.h&gt;</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="centroid_8h.html">pcl/common/centroid.h</a>&gt;</span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#include &lt;pcl/common/concatenate.h&gt;</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#aafc02bea3d135d035c3304ddb7bf694b">   50</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#aafc02bea3d135d035c3304ddb7bf694b">pcl::SampleConsensusModelLine&lt;PointT&gt;::isSampleGood</a> (<span class="keyword">const</span> std::vector&lt;int&gt; &amp;samples)<span class="keyword"> const</span></div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;  <span class="keywordflow">if</span> (</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;      (input_-&gt;points[samples[0]].x != input_-&gt;points[samples[1]].x)</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    &amp;&amp;</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;      (input_-&gt;points[samples[0]].y != input_-&gt;points[samples[1]].y)</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    &amp;&amp;</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;      (input_-&gt;points[samples[0]].z != input_-&gt;points[samples[1]].z))</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160; </div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;}</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#a2c09de6c3d95758f25c1942ac7a050f9">   65</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#a2c09de6c3d95758f25c1942ac7a050f9">pcl::SampleConsensusModelLine&lt;PointT&gt;::computeModelCoefficients</a> (</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;      <span class="keyword">const</span> std::vector&lt;int&gt; &amp;samples, Eigen::VectorXf &amp;model_coefficients)</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;{</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  <span class="comment">// Need 2 samples</span></div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  <span class="keywordflow">if</span> (samples.size () != 2)</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  {</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::SampleConsensusModelLine::computeModelCoefficients] Invalid set of samples given (%lu)!\n&quot;</span>, samples.size ());</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;  }</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160; </div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  <span class="keywordflow">if</span> (fabs (input_-&gt;points[samples[0]].x - input_-&gt;points[samples[1]].x) &lt;= std::numeric_limits&lt;float&gt;::epsilon () &amp;&amp; </div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;      fabs (input_-&gt;points[samples[0]].y - input_-&gt;points[samples[1]].y) &lt;= std::numeric_limits&lt;float&gt;::epsilon () &amp;&amp; </div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;      fabs (input_-&gt;points[samples[0]].z - input_-&gt;points[samples[1]].z) &lt;= std::numeric_limits&lt;float&gt;::epsilon ())</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;  {</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  }</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  model_coefficients.resize (6);</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  model_coefficients[0] = input_-&gt;points[samples[0]].x;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;  model_coefficients[1] = input_-&gt;points[samples[0]].y;</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  model_coefficients[2] = input_-&gt;points[samples[0]].z;</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160; </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  model_coefficients[3] = input_-&gt;points[samples[1]].x - model_coefficients[0];</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;  model_coefficients[4] = input_-&gt;points[samples[1]].y - model_coefficients[1];</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  model_coefficients[5] = input_-&gt;points[samples[1]].z - model_coefficients[2];</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160; </div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  model_coefficients.template tail&lt;3&gt; ().normalize ();</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;}</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#a68b282649799eac370616e9ab124c970">   97</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#a68b282649799eac370616e9ab124c970">pcl::SampleConsensusModelLine&lt;PointT&gt;::getDistancesToModel</a> (</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;      <span class="keyword">const</span> Eigen::VectorXf &amp;model_coefficients, std::vector&lt;double&gt; &amp;distances)</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;{</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;  <span class="comment">// Needs a valid set of model coefficients</span></div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;  <span class="keywordflow">if</span> (!isModelValid (model_coefficients))</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;  distances.resize (indices_-&gt;size ());</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160; </div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;  <span class="comment">// Obtain the line point and direction</span></div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;  Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;  Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;  line_dir.normalize ();</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160; </div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the line</span></div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; indices_-&gt;size (); ++i)</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;  {</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    <span class="comment">// Calculate the distance from the point to the line</span></div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="comment">// D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    <span class="comment">// Need to estimate sqrt here to keep MSAC and friends general</span></div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    distances[i] = sqrt ((line_pt - input_-&gt;points[(*indices_)[i]].getVector4fMap ()).cross3 (line_dir).squaredNorm ());</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;  }</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;}</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160; </div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00123"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#a1204c9998433ce3b8b1e20240085df66">  123</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#a1204c9998433ce3b8b1e20240085df66">pcl::SampleConsensusModelLine&lt;PointT&gt;::selectWithinDistance</a> (</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;      <span class="keyword">const</span> Eigen::VectorXf &amp;model_coefficients, <span class="keyword">const</span> <span class="keywordtype">double</span> threshold, std::vector&lt;int&gt; &amp;inliers)</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;{</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  <span class="comment">// Needs a valid set of model coefficients</span></div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;  <span class="keywordflow">if</span> (!isModelValid (model_coefficients))</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160; </div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  <span class="keywordtype">double</span> sqr_threshold = threshold * threshold;</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160; </div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;  <span class="keywordtype">int</span> nr_p = 0;</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;  inliers.resize (indices_-&gt;size ());</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;  error_sqr_dists_.resize (indices_-&gt;size ());</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160; </div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;  <span class="comment">// Obtain the line point and direction</span></div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  line_dir.normalize ();</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160; </div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the line</span></div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; indices_-&gt;size (); ++i)</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  {</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <span class="comment">// Calculate the distance from the point to the line</span></div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <span class="comment">// D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)</span></div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <span class="keywordtype">double</span> sqr_distance = (line_pt - input_-&gt;points[(*indices_)[i]].getVector4fMap ()).cross3 (line_dir).squaredNorm ();</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160; </div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordflow">if</span> (sqr_distance &lt; sqr_threshold)</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    {</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;      <span class="comment">// Returns the indices of the points whose squared distances are smaller than the threshold</span></div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;      inliers[nr_p] = (*indices_)[i];</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;      error_sqr_dists_[nr_p] = sqr_distance;</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;      ++nr_p;</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    }</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  }</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;  inliers.resize (nr_p);</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  error_sqr_dists_.resize (nr_p);</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;}</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160; </div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">int</span></div>
<div class="line"><a name="l00162"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#a2885d3c4271f8cb8aed6ebc34c65d994">  162</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#a2885d3c4271f8cb8aed6ebc34c65d994">pcl::SampleConsensusModelLine&lt;PointT&gt;::countWithinDistance</a> (</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      <span class="keyword">const</span> Eigen::VectorXf &amp;model_coefficients, <span class="keyword">const</span> <span class="keywordtype">double</span> threshold)</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;{</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  <span class="comment">// Needs a valid set of model coefficients</span></div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;  <span class="keywordflow">if</span> (!isModelValid (model_coefficients))</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    <span class="keywordflow">return</span> (0);</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160; </div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;  <span class="keywordtype">double</span> sqr_threshold = threshold * threshold;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160; </div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  <span class="keywordtype">int</span> nr_p = 0;</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  <span class="comment">// Obtain the line point and direction</span></div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;  Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;  line_dir.normalize ();</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160; </div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the line</span></div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; indices_-&gt;size (); ++i)</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  {</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    <span class="comment">// Calculate the distance from the point to the line</span></div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    <span class="comment">// D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)</span></div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="keywordtype">double</span> sqr_distance = (line_pt - input_-&gt;points[(*indices_)[i]].getVector4fMap ()).cross3 (line_dir).squaredNorm ();</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160; </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    <span class="keywordflow">if</span> (sqr_distance &lt; sqr_threshold)</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;      nr_p++;</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  }</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  <span class="keywordflow">return</span> (nr_p);</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;}</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160; </div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#ad29efa5e1fc75c814612f5c4926233ef">  193</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#ad29efa5e1fc75c814612f5c4926233ef">pcl::SampleConsensusModelLine&lt;PointT&gt;::optimizeModelCoefficients</a> (</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;      <span class="keyword">const</span> std::vector&lt;int&gt; &amp;inliers, <span class="keyword">const</span> Eigen::VectorXf &amp;model_coefficients, Eigen::VectorXf &amp;optimized_coefficients)</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;{</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  <span class="comment">// Needs a valid set of model coefficients</span></div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;  <span class="keywordflow">if</span> (!isModelValid (model_coefficients))</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  {</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    optimized_coefficients = model_coefficients;</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;  }</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160; </div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;  <span class="comment">// Need at least 2 points to estimate a line</span></div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;  <span class="keywordflow">if</span> (inliers.size () &lt;= 2)</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;  {</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::SampleConsensusModelLine::optimizeModelCoefficients] Not enough inliers found to support a model (%lu)! Returning the same coefficients.\n&quot;</span>, inliers.size ());</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    optimized_coefficients = model_coefficients;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;  }</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;  optimized_coefficients.resize (6);</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160; </div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;  <span class="comment">// Compute the 3x3 covariance matrix</span></div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;  Eigen::Vector4f centroid;</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (*input_, inliers, centroid);</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;  Eigen::Matrix3f covariance_matrix;</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (*input_, inliers, centroid, covariance_matrix);</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  optimized_coefficients[0] = centroid[0];</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;  optimized_coefficients[1] = centroid[1];</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;  optimized_coefficients[2] = centroid[2];</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160; </div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  <span class="comment">// Extract the eigenvalues and eigenvectors</span></div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  EIGEN_ALIGN16 Eigen::Vector3f eigen_values;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  EIGEN_ALIGN16 Eigen::Vector3f eigen_vector;</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  <a class="code" href="group__common.html#gaca873868052e7d26efcf4b684a17bef2">pcl::eigen33</a> (covariance_matrix, eigen_values);</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;  <a class="code" href="group__common.html#ga11c9b186d04d2e8a868e058473214622">pcl::computeCorrespondingEigenVector</a> (covariance_matrix, eigen_values [2], eigen_vector);</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;  <span class="comment">//pcl::eigen33 (covariance_matrix, eigen_vectors, eigen_values);</span></div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160; </div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;  optimized_coefficients.template tail&lt;3&gt; ().matrix () = eigen_vector;</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;}</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160; </div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#afc373efb74ec6e2c4761a5714b54b316">  234</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#afc373efb74ec6e2c4761a5714b54b316">pcl::SampleConsensusModelLine&lt;PointT&gt;::projectPoints</a> (</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;      <span class="keyword">const</span> std::vector&lt;int&gt; &amp;inliers, <span class="keyword">const</span> Eigen::VectorXf &amp;model_coefficients, <a class="code" href="classpcl_1_1_point_cloud.html">PointCloud</a> &amp;projected_points, <span class="keywordtype">bool</span> copy_data_fields)</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;{</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;  <span class="comment">// Needs a valid model coefficients</span></div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;  <span class="keywordflow">if</span> (!isModelValid (model_coefficients))</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160; </div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  <span class="comment">// Obtain the line point and direction</span></div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;  Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;  Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160; </div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">header</a> = input_-&gt;header;</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;  projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a3ca88d8ebf6f4f35acbc31cdfb38aa94">is_dense</a> = input_-&gt;is_dense;</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160; </div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  <span class="comment">// Copy all the data fields from the input cloud to the projected one?</span></div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;  <span class="keywordflow">if</span> (copy_data_fields)</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;  {</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <span class="comment">// Allocate enough space and copy the basics</span></div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.resize (input_-&gt;points.size ());</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a>    = input_-&gt;width;</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a>   = input_-&gt;height;</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160; </div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structpcl_1_1traits_1_1field_list.html">pcl::traits::fieldList&lt;PointT&gt;::type</a> FieldList;</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <span class="comment">// Iterate over each point</span></div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.size (); ++i)</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;      <span class="comment">// Iterate over each dimension</span></div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;      pcl::for_each_type &lt;FieldList&gt; (<a class="code" href="structpcl_1_1_nd_concatenate_functor.html">NdConcatenateFunctor &lt;PointT, PointT&gt;</a> (input_-&gt;points[i], projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i]));</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160; </div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    <span class="comment">// Iterate through the 3d points and calculate the distances from them to the line</span></div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; inliers.size (); ++i)</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;    {</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;      Eigen::Vector4f pt (input_-&gt;points[inliers[i]].x, input_-&gt;points[inliers[i]].y, input_-&gt;points[inliers[i]].z, 0);</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;      <span class="comment">// double k = (DOT_PROD_3D (points[i], p21) - dotA_B) / dotB_B;</span></div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;      <span class="keywordtype">float</span> k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160; </div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;      Eigen::Vector4f pp = line_pt + k * line_dir;</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;      <span class="comment">// Calculate the projection of the point on the line (pointProj = A + k * B)</span></div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[inliers[i]].x = pp[0];</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[inliers[i]].y = pp[1];</div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[inliers[i]].z = pp[2];</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    }</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;  }</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;  {</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;    <span class="comment">// Allocate enough space and copy the basics</span></div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;    projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>.resize (inliers.size ());</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">width</a>    = <span class="keyword">static_cast&lt;</span>uint32_t<span class="keyword">&gt;</span> (inliers.size ());</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;    projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">height</a>   = 1;</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160; </div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code" href="structpcl_1_1traits_1_1field_list.html">pcl::traits::fieldList&lt;PointT&gt;::type</a> FieldList;</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;    <span class="comment">// Iterate over each point</span></div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; inliers.size (); ++i)</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;      <span class="comment">// Iterate over each dimension</span></div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;      pcl::for_each_type &lt;FieldList&gt; (<a class="code" href="structpcl_1_1_nd_concatenate_functor.html">NdConcatenateFunctor &lt;PointT, PointT&gt;</a> (input_-&gt;points[inliers[i]], projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i]));</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160; </div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;    <span class="comment">// Iterate through the 3d points and calculate the distances from them to the line</span></div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; inliers.size (); ++i)</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    {</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;      Eigen::Vector4f pt (input_-&gt;points[inliers[i]].x, input_-&gt;points[inliers[i]].y, input_-&gt;points[inliers[i]].z, 0);</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;      <span class="comment">// double k = (DOT_PROD_3D (points[i], p21) - dotA_B) / dotB_B;</span></div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;      <span class="keywordtype">float</span> k = (pt.dot (line_dir) - line_pt.dot (line_dir)) / line_dir.dot (line_dir);</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160; </div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;      Eigen::Vector4f pp = line_pt + k * line_dir;</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;      <span class="comment">// Calculate the projection of the point on the line (pointProj = A + k * B)</span></div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].x = pp[0];</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].y = pp[1];</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;      projected_points.<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[i].z = pp[2];</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    }</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;  }</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;}</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160; </div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">bool</span></div>
<div class="line"><a name="l00307"></a><span class="lineno"><a class="line" href="classpcl_1_1_sample_consensus_model_line.html#a46511a245836abd6d73fd924f2a4f285">  307</a></span>&#160;<a class="code" href="classpcl_1_1_sample_consensus_model_line.html#a46511a245836abd6d73fd924f2a4f285">pcl::SampleConsensusModelLine&lt;PointT&gt;::doSamplesVerifyModel</a> (</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;      <span class="keyword">const</span> std::set&lt;int&gt; &amp;indices, <span class="keyword">const</span> Eigen::VectorXf &amp;model_coefficients, <span class="keyword">const</span> <span class="keywordtype">double</span> threshold)</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;{</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;  <span class="comment">// Needs a valid set of model coefficients</span></div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  <span class="keywordflow">if</span> (!isModelValid (model_coefficients))</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160; </div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;  <span class="comment">// Obtain the line point and direction</span></div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;  Eigen::Vector4f line_pt  (model_coefficients[0], model_coefficients[1], model_coefficients[2], 0);</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;  Eigen::Vector4f line_dir (model_coefficients[3], model_coefficients[4], model_coefficients[5], 0);</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;  line_dir.normalize ();</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160; </div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;  <span class="keywordtype">double</span> sqr_threshold = threshold * threshold;</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;  <span class="comment">// Iterate through the 3d points and calculate the distances from them to the line</span></div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;  <span class="keywordflow">for</span> (std::set&lt;int&gt;::const_iterator it = indices.begin (); it != indices.end (); ++it)</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  {</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    <span class="comment">// Calculate the distance from the point to the line</span></div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    <span class="comment">// D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p2-p0)) / norm(p2-p1)</span></div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    <span class="keywordflow">if</span> ((line_pt - input_-&gt;points[*it].getVector4fMap ()).cross3 (line_dir).squaredNorm () &gt; sqr_threshold)</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;      <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;  }</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160; </div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;}</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160; </div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;<span class="preprocessor">#define PCL_INSTANTIATE_SampleConsensusModelLine(T) template class PCL_EXPORTS pcl::SampleConsensusModelLine&lt;T&gt;;</span></div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160; </div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;<span class="preprocessor">#endif    </span><span class="comment">// PCL_SAMPLE_CONSENSUS_IMPL_SAC_MODEL_LINE_H_</span></div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160; </div>
<div class="ttc" id="acentroid_8h_html"><div class="ttname"><a href="centroid_8h.html">centroid.h</a></div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud</a></div><div class="ttdoc">PointCloud represents the base class in PCL for storing collections of 3D points.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:173</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a2185a6453f8ad905d7bdf7b45754a160"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a2185a6453f8ad905d7bdf7b45754a160">pcl::PointCloud::width</a></div><div class="ttdeci">uint32_t width</div><div class="ttdoc">The point cloud width (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:413</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a3ca88d8ebf6f4f35acbc31cdfb38aa94"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a3ca88d8ebf6f4f35acbc31cdfb38aa94">pcl::PointCloud::is_dense</a></div><div class="ttdeci">bool is_dense</div><div class="ttdoc">True if no points are invalid (e.g., have NaN or Inf values).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:418</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a4f34b45220c57f96607513ffad0d9582"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a4f34b45220c57f96607513ffad0d9582">pcl::PointCloud::height</a></div><div class="ttdeci">uint32_t height</div><div class="ttdoc">The point cloud height (if organized as an image-structure).</div><div class="ttdef"><b>Definition:</b> point_cloud.h:415</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_a82e0be055a617e5e74102ed62712b352"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#a82e0be055a617e5e74102ed62712b352">pcl::PointCloud::header</a></div><div class="ttdeci">pcl::PCLHeader header</div><div class="ttdoc">The point cloud header. It contains information about the acquisition time.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:407</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_a1204c9998433ce3b8b1e20240085df66"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#a1204c9998433ce3b8b1e20240085df66">pcl::SampleConsensusModelLine::selectWithinDistance</a></div><div class="ttdeci">void selectWithinDistance(const Eigen::VectorXf &amp;model_coefficients, const double threshold, std::vector&lt; int &gt; &amp;inliers)</div><div class="ttdoc">Select all the points which respect the given model coefficients as inliers.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:123</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_a2885d3c4271f8cb8aed6ebc34c65d994"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#a2885d3c4271f8cb8aed6ebc34c65d994">pcl::SampleConsensusModelLine::countWithinDistance</a></div><div class="ttdeci">virtual int countWithinDistance(const Eigen::VectorXf &amp;model_coefficients, const double threshold)</div><div class="ttdoc">Count all the points which respect the given model coefficients as inliers.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:162</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_a2c09de6c3d95758f25c1942ac7a050f9"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#a2c09de6c3d95758f25c1942ac7a050f9">pcl::SampleConsensusModelLine::computeModelCoefficients</a></div><div class="ttdeci">bool computeModelCoefficients(const std::vector&lt; int &gt; &amp;samples, Eigen::VectorXf &amp;model_coefficients)</div><div class="ttdoc">Check whether the given index samples can form a valid line model, compute the model coefficients fro...</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:65</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_a46511a245836abd6d73fd924f2a4f285"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#a46511a245836abd6d73fd924f2a4f285">pcl::SampleConsensusModelLine::doSamplesVerifyModel</a></div><div class="ttdeci">bool doSamplesVerifyModel(const std::set&lt; int &gt; &amp;indices, const Eigen::VectorXf &amp;model_coefficients, const double threshold)</div><div class="ttdoc">Verify whether a subset of indices verifies the given line model coefficients.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:307</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_a68b282649799eac370616e9ab124c970"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#a68b282649799eac370616e9ab124c970">pcl::SampleConsensusModelLine::getDistancesToModel</a></div><div class="ttdeci">void getDistancesToModel(const Eigen::VectorXf &amp;model_coefficients, std::vector&lt; double &gt; &amp;distances)</div><div class="ttdoc">Compute all squared distances from the cloud data to a given line model.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:97</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_aafc02bea3d135d035c3304ddb7bf694b"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#aafc02bea3d135d035c3304ddb7bf694b">pcl::SampleConsensusModelLine::isSampleGood</a></div><div class="ttdeci">bool isSampleGood(const std::vector&lt; int &gt; &amp;samples) const</div><div class="ttdoc">Check if a sample of indices results in a good sample of points indices.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:50</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_ad29efa5e1fc75c814612f5c4926233ef"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#ad29efa5e1fc75c814612f5c4926233ef">pcl::SampleConsensusModelLine::optimizeModelCoefficients</a></div><div class="ttdeci">void optimizeModelCoefficients(const std::vector&lt; int &gt; &amp;inliers, const Eigen::VectorXf &amp;model_coefficients, Eigen::VectorXf &amp;optimized_coefficients)</div><div class="ttdoc">Recompute the line coefficients using the given inlier set and return them to the user.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:193</div></div>
<div class="ttc" id="aclasspcl_1_1_sample_consensus_model_line_html_afc373efb74ec6e2c4761a5714b54b316"><div class="ttname"><a href="classpcl_1_1_sample_consensus_model_line.html#afc373efb74ec6e2c4761a5714b54b316">pcl::SampleConsensusModelLine::projectPoints</a></div><div class="ttdeci">void projectPoints(const std::vector&lt; int &gt; &amp;inliers, const Eigen::VectorXf &amp;model_coefficients, PointCloud &amp;projected_points, bool copy_data_fields=true)</div><div class="ttdoc">Create a new point cloud with inliers projected onto the line model.</div><div class="ttdef"><b>Definition:</b> sac_model_line.hpp:234</div></div>
<div class="ttc" id="agroup__common_html_ga11c9b186d04d2e8a868e058473214622"><div class="ttname"><a href="group__common.html#ga11c9b186d04d2e8a868e058473214622">pcl::computeCorrespondingEigenVector</a></div><div class="ttdeci">void computeCorrespondingEigenVector(const Matrix &amp;mat, const typename Matrix::Scalar &amp;eigenvalue, Vector &amp;eigenvector)</div><div class="ttdoc">determines the corresponding eigenvector to the given eigenvalue of the symmetric positive semi defin...</div><div class="ttdef"><b>Definition:</b> eigen.hpp:219</div></div>
<div class="ttc" id="agroup__common_html_gac36b146ec26b1ceb7be43a9ecaa010c4"><div class="ttname"><a href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">pcl::computeCovarianceMatrix</a></div><div class="ttdeci">unsigned int computeCovarianceMatrix(const pcl::PointCloud&lt; PointT &gt; &amp;cloud, const Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid, Eigen::Matrix&lt; Scalar, 3, 3 &gt; &amp;covariance_matrix)</div><div class="ttdoc">Compute the 3x3 covariance matrix of a given set of points. The result is returned as a Eigen::Matrix...</div></div>
<div class="ttc" id="agroup__common_html_gaca873868052e7d26efcf4b684a17bef2"><div class="ttname"><a href="group__common.html#gaca873868052e7d26efcf4b684a17bef2">pcl::eigen33</a></div><div class="ttdeci">void eigen33(const Matrix &amp;mat, typename Matrix::Scalar &amp;eigenvalue, Vector &amp;eigenvector)</div><div class="ttdoc">determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi d...</div><div class="ttdef"><b>Definition:</b> eigen.hpp:251</div></div>
<div class="ttc" id="agroup__common_html_gaf5729fae15603888b49743b118025290"><div class="ttname"><a href="group__common.html#gaf5729fae15603888b49743b118025290">pcl::compute3DCentroid</a></div><div class="ttdeci">unsigned int compute3DCentroid(ConstCloudIterator&lt; PointT &gt; &amp;cloud_iterator, Eigen::Matrix&lt; Scalar, 4, 1 &gt; &amp;centroid)</div><div class="ttdoc">Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.</div><div class="ttdef"><b>Definition:</b> centroid.hpp:50</div></div>
<div class="ttc" id="astructpcl_1_1_nd_concatenate_functor_html"><div class="ttname"><a href="structpcl_1_1_nd_concatenate_functor.html">pcl::NdConcatenateFunctor</a></div><div class="ttdoc">Helper functor structure for concatenate.</div><div class="ttdef"><b>Definition:</b> concatenate.h:65</div></div>
<div class="ttc" id="astructpcl_1_1traits_1_1field_list_html"><div class="ttname"><a href="structpcl_1_1traits_1_1field_list.html">pcl::traits::fieldList</a></div><div class="ttdef"><b>Definition:</b> point_traits.h:177</div></div>
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